Introduction
Welcome to my research page. I am a dedicated researcher with a profound passion for applied machine learning and its vast applications in the fields of materials science, computational chemistry, and computational physics. In my current research endeavors, I am focused on leveraging the potential of machine learning algorithms to drive significant advancements in materials discovery and unravel the intricate behaviors of proteins at interfaces. Additionally, I am actively exploring the emerging field of quantum machine learning, seeking to harness the unique capabilities of quantum computing for enhanced data analysis and modeling. By harnessing the capabilities of quantum computing, I seek to demonstrate the superior advantages of quantum machine learning over classical approaches, particularly in terms of training speed, prediction accuracy, and model expressiveness.
One of the primary areas of my research revolves around utilizing machine learning techniques to expedite the process of materials discovery. By leveraging advanced algorithms, I aim to identify novel materials with desirable properties, revolutionizing industries such as energy storage, drug discovery, and catalysis. Additionally, I have delved into the fascinating realm of protein structure transition trajectory studies, employing machine learning to unravel the complex mechanisms underlying protein folding and dynamics.
I have had the privilege of collaborating with researchers from institutions such as Arizona State University, the University of Texas at Austin, University of South Carolina, Howard University, the City University of New York, Wake Forest University, Kennesaw State University, Brookhaven National Laboratory, Sandia National Laboratory, NASA Jet Propulsion Laboratory, and the Joint School of Nanoscience and Nanoengineering, which comprises the University of North Carolina at Greensboro and North Carolina A&T University.
Despite my demanding teaching schedule, I have been actively involved in disseminating my findings through scholarly publications. To date, I have contributed over thirty papers to esteemed journals and international conference proceedings, including Journal of Chemical Theory and Computation, ACS LANGMUIR, Applied Physics Letters, ACS Journal of Physical Chemistry(b), ACM Multimedia Conference, IEEE Trans. on Multimedia, ACM Trans. on Multimedia Computing, Communications and Applications, and IEEE International Conference on Machine Learning and Applications.
I am excited to continue my journey as a researcher, unraveling the possibilities that lie at the intersection of machine learning and the physical sciences.